1 Risk and Reliability Analysis of a Subsea System for Oil Production Keith Dillian Schneider Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal The present project was accomplished with the support of CNPq, Conselho Nacional de Desenvolvimento Científico e Tecnológico – Brasil. ABSTRACT: There are many layouts for offshore oil and gas production that can be implemented that differ on the topside and subsea equipment. When applying new technologies in subsea production systems there is few information in conceptual design, regarding sizes of equipment, capacities, failure statistics, among others. The objective of this work is to present a model to assess the risk and reliability of subsea equipment used in offshore oil production fields. Two scenarios of offshore production layout are compared in terms of risks and reliability: conventional and hybrid scenarios. The conventional scenario separates water and gas from oil in a topside system of a floating production storage and offloading (FPSO), while the hybrid scenario uses a subsea separator that allows the water to be reinjected into the well without being lifted together with the well fluid, letting more space available in the FPSO for oil storage. Simplified reliability models are presented for the subsea separator, pumps, flowlines and risers. As there is not enough failure data to characterize the reliability of the subsea separator, a methodology is applied to predict its reliability using information from a similar topside separator. The reliability prediction approach is illustrated with a case study of an oil field located in Brazil. 1 INTRODUCTION With the increasing of energy demand and production, new subsea technology is constantly being implemented in offshore production. Innovation is only limited by costs and permissible risks the project can be exposed to. Risk analysis has a major importance in offshore industry. Not only the costs of an accident can be expressively high, or environment can be strongly affected, but lives are exposed, which increases the social responsibility in offshore operations. Christou and Konstantinidou (2012) also emphasize the indirect economic consequences, using as example the accident of Deepwater Horizon, in which the company had losses from the fail in price of shares (shares have fallen around 50% in June 2010). Risk analysis can be used as a decision supporting tool to improve conceptual design. However, this analysis requires failure data from equipment that are not available for new equipment or equipment that will work in different environmental conditions, such as at the subsea. In conceptual design stage is normal to have many assumptions and proportionally many uncertainties. The design team has an idea of what kind of equipment can be implemented, but not enough information regarding sizes, capacities and costs. Added to that, when the project has innovation this task probably has more uncertainties. According to Duan et al. (2018), subsea production systems are important for exploitation of offshore oil and gas, as an efficient and cost-effective plan for deepwater fields. The challenge of new technology is to find information to predict their reliability. As offshore equipment is designed to have a long life, equipment does not fail in such frequency in order to provide trustworthy conclusions from statistics. Because of that, statistics of reliability data such as OREDA (Offshore Reliability Data), SINTEF (2002); Handbook of Reliability Prediction Procedures for Mechanical Equipment, LTS (2010); and Guidelines for process equipment reliability data, AIChE (1988), may not be sufficient to make a reasonable prediction, and methodologies are being implemented with the objective to predict failure rates of new subsea equipment based on existing similar topside equipment. The objective of this thesis is to present a model to assess the risk and reliability of subsea equipment used in offshore fields for oil production. 2 RISK ANALYSIS APPLIED IN OFFSHORE INDUSTRY Brandsæter (2002) analyzes the implementation of risk assessment in the offshore industry, with focus on safety aspects, and in quantitative risk assessment. Based on a research with professionals in the field, it was indicated that the perception of risk in offshore industry is not uniform. While the extent of potential damage is high, the probability of occurrence and uncertainties perception are ranged from low to medium. Yasseri and Bahai (2018) calculated the availability of a subsea distribution plant at the design stage using as reliability tool DSM. The access of failure rate of equipment was directly made using OREDA (2002), considering that the failure rates of equipment is constant, which could be a source of error in analysis, but in the architecture level of design is acceptable, regarding the available data is scarce. Also, some assumptions for the modelling were made, and must be updated as the design progresses. It is known that for risk and reliability analysis reliability data of the components and systems are necessary to properly evaluate the design or operation. In some cases, the studies and projects must be developed not having total access to reliability data, and for that there are some tools that can be used to predict the failure characteristics of the equipment to overcome the lack of data. The method BORA-release, by Sklet et al. (2006) analyzes the hydrocarbon release frequency, taking into account the effect of the safety barriers used for release prevention. The method also analyzes the influence of RIFs (Reliability Influence Factor) - as technical, human, operational and organizational conditions- in the barriers performance. One challenge of this method is the lack of input data available, especially in human reliability in the offshore field. Vinnem et al. (2009) applied the BORA method in a study case related to an offshore oil and gas production platform. The
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1
Risk and Reliability Analysis of a Subsea System for Oil Production
Keith Dillian Schneider
Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
The present project was accomplished with the support of CNPq, Conselho Nacional de Desenvolvimento Científico e Tecnológico – Brasil.
ABSTRACT: There are many layouts for offshore oil and gas production that can be implemented that differ on the topside and
subsea equipment. When applying new technologies in subsea production systems there is few information in conceptual design,
regarding sizes of equipment, capacities, failure statistics, among others. The objective of this work is to present a model to assess
the risk and reliability of subsea equipment used in offshore oil production fields. Two scenarios of offshore production layout are
compared in terms of risks and reliability: conventional and hybrid scenarios. The conventional scenario separates water and gas
from oil in a topside system of a floating production storage and offloading (FPSO), while the hybrid scenario uses a subsea separator
that allows the water to be reinjected into the well without being lifted together with the well fluid, letting more space available in
the FPSO for oil storage. Simplified reliability models are presented for the subsea separator, pumps, flowlines and risers. As there
is not enough failure data to characterize the reliability of the subsea separator, a methodology is applied to predict its reliability
using information from a similar topside separator. The reliability prediction approach is illustrated with a case study of an oil field
located in Brazil.
1 INTRODUCTION
With the increasing of energy demand and production, new
subsea technology is constantly being implemented in offshore
production. Innovation is only limited by costs and permissible
risks the project can be exposed to.
Risk analysis has a major importance in offshore industry. Not
only the costs of an accident can be expressively high, or
environment can be strongly affected, but lives are exposed,
which increases the social responsibility in offshore operations.
Christou and Konstantinidou (2012) also emphasize the indirect
economic consequences, using as example the accident of
Deepwater Horizon, in which the company had losses from the
fail in price of shares (shares have fallen around 50% in June
2010).
Risk analysis can be used as a decision supporting tool to
improve conceptual design. However, this analysis requires
failure data from equipment that are not available for new
equipment or equipment that will work in different
environmental conditions, such as at the subsea. In conceptual
design stage is normal to have many assumptions and
proportionally many uncertainties. The design team has an idea
of what kind of equipment can be implemented, but not enough
information regarding sizes, capacities and costs. Added to that,
when the project has innovation this task probably has more
uncertainties. According to Duan et al. (2018), subsea
production systems are important for exploitation of offshore oil
and gas, as an efficient and cost-effective plan for deepwater
fields. The challenge of new technology is to find information
to predict their reliability. As offshore equipment is designed to
have a long life, equipment does not fail in such frequency in
order to provide trustworthy conclusions from statistics.
Because of that, statistics of reliability data such as OREDA
(Offshore Reliability Data), SINTEF (2002); Handbook of
Reliability Prediction Procedures for Mechanical Equipment,
LTS (2010); and Guidelines for process equipment reliability
data, AIChE (1988), may not be sufficient to make a reasonable
prediction, and methodologies are being implemented with the
objective to predict failure rates of new subsea equipment based
on existing similar topside equipment.
The objective of this thesis is to present a model to assess the
risk and reliability of subsea equipment used in offshore fields
for oil production.
2 RISK ANALYSIS APPLIED IN
OFFSHORE INDUSTRY
Brandsæter (2002) analyzes the implementation of risk
assessment in the offshore industry, with focus on safety
aspects, and in quantitative risk assessment. Based on a research
with professionals in the field, it was indicated that the
perception of risk in offshore industry is not uniform. While the
extent of potential damage is high, the probability of occurrence
and uncertainties perception are ranged from low to medium.
Yasseri and Bahai (2018) calculated the availability of a subsea
distribution plant at the design stage using as reliability tool
DSM. The access of failure rate of equipment was directly made
using OREDA (2002), considering that the failure rates of
equipment is constant, which could be a source of error in
analysis, but in the architecture level of design is acceptable,
regarding the available data is scarce. Also, some assumptions
for the modelling were made, and must be updated as the design
progresses.
It is known that for risk and reliability analysis reliability data
of the components and systems are necessary to properly
evaluate the design or operation. In some cases, the studies and
projects must be developed not having total access to reliability
data, and for that there are some tools that can be used to predict
the failure characteristics of the equipment to overcome the lack
of data.
The method BORA-release, by Sklet et al. (2006) analyzes the
hydrocarbon release frequency, taking into account the effect of
the safety barriers used for release prevention. The method also
analyzes the influence of RIFs (Reliability Influence Factor) -
as technical, human, operational and organizational conditions-
in the barriers performance. One challenge of this method is the
lack of input data available, especially in human reliability in
the offshore field.
Vinnem et al. (2009) applied the BORA method in a study case
related to an offshore oil and gas production platform. The
2
situations in which the method would be applied were decided
in discussions between personnel from the oil company and
project team members, and it was decided to apply it in three
situations: release due to valve(s) in wrong position after
maintenance (A), release due to incorrect fitting of flanges or
bolts during maintenance (B), and release due to internal
corrosion (C). The results for situations A and B presented
higher release frequencies when compared with industry
average data, which is explained by the status of several of the
RIFs measured by the RNNS-data was worse than the industry
average standard. The quantitative results for scenarios A and B
were reasonable compared to release statistics. A question is
raised regarding how specific the assessment of the status of
RIFs needs to be. Results for scenario C did not presented the
same confidence from results of scenarios A and B, because the
phenomenon of corrosion is complex, and the assumptions
made for this work must be discussed. Sensitivity analyses
performed in the study supported the conclusion that the method
can a useful tool to analyses the effect on the release frequency
of safety barriers introduced to prevent hydrocarbon releases.
Rahimi and Rausand (2013) proposed an approach to determine
the failure rates of new subsea systems, making a detailed
comparison with the topside systems. Being subsea systems
adapted from topside systems, the reliability information cannot
be used directly for subsea design, due to design modifications,
different environmental stresses and maintenance. A reliability
data for topside systems are typically available, the approach
applied RIFs to analyze subsea systems.
Abdelmalek (2018), performed a semi-quantitative risk
assessment of a subsea production system in the conceptual
phase. It was used as tool the concept of RIFs to applicate in
subsea equipment, and ETA, linking the end terminals with
different consequence groups, denotating quantified
magnitudes of consequences. A practical demonstration is made
applying semi-quantitative risk assessment in an offshore field
located in Brazil.
A study conducted by Silva (2016) analyzed the relevance of
risk analysis in operational safety regarding subsea pipelines for
transport systems. A tool from DNV (2009) was used to
calculate failure rates for two case studies in North Sea,
considering not just the failure modes, but also a number of
factors that influence the likelihood of failure, such as age, size,
length of line and location. As a result, both cases revealed that
the failure frequency was directly proportional on the size
length.
3 METHODOLOGY
According to Rausand and Høyland (2004), in a qualitative risk
analysis, probabilities and consequences are determined purely
by qualitative characteristics,. As presented in the previous
chapter, there are several tools for qualitative analysis. In this
project the FMEA method is selected for a preliminary analysis
of the subsea production concept.
FMEA is a tool that can be used to acquire an overview of types
of failures that can happen in the system, their consequence, and
helps to determine ways to minimize their occurrence. It can be
implemented for systems functions, subsystems or components.
Quantitative risk analysis gives numerical estimates of
probabilities and consequences, and eventually these estimates
have some uncertainties, according to Rausand and Høyland
(2004). This approach is best suited for risk associated with low
probability of occurrence and high consequence events.
Reliability is defined as a characteristic of the ability of a
component or a system to perform a specific function (Aven,
1992). Important measures of the reliability of a nonrepairable
component are: reliability function 𝑅(𝑡), failure rate function
𝑧(𝑡) , and mean time to failure 𝑀𝑇𝑇𝐹 . To access this
information many distributions can be used, depending on data
available and failure modes, as exponential distribution,